Mechanisms of Network Changes in Cognitive Impairment in Multiple Sclerosis

Investigating the impact of different dichotomous definitions for cognitive impairment on functional connectivity in secondary progressive MS

BACKGROUND

Altered brain network function is associated with cognitive impairment in multiple sclerosis (MS), but recent studies highlight a lack of consensus in the field. These differences may relate to the stage of MS, or different definitions for cognitive impairment.

OBJECTIVE

We investigated cognitive impairment and functional connectivity (FC) specifically in SPMS (secondary progressive MS) using resting-state functional MRI (rs-fMRI) and assessed the alterations in FC using two commonly used dichotomous criteria for cognitive impairment.

METHODS

65 SPMS subjects from a British cohort underwent rs-fMRI at 3T, with independent component analysis of resting state networks. Cognitive impairment, assessed by neuropsychometry, was defined using a z-score of ≤ -1.96SD on ≥ 2 domains (-1.96SD group) or z-score of ≤ -1.5SD on ≥ 2 domains (-1.5SD group).

RESULTS

Cognitive impairment was, as expected, more prevalent in the -1.5SD (47 %) than -1.96SD criteria (30 %) group, despite similar demographics in both; mean age of 55 ± 7.1 years, disease duration 22 ± 9.6 years, median EDSS of 6.0 [range 4.0-6.5]. Adopting the -1.96SD criteria substantially increased the number of altered brain regions, with a 2.8 fold increase in regions showing decreased FC; including the ventral attentional and sensorimotor networks, and 1.5 fold increase in regions showing increased FC; including the precuneus and auditory networks.

CONCLUSIONS

The criteria chosen for cognitive impairment significantly impacts patterns of global FC change and may miss key network alterations, which could impact the efficacy of future therapeutic interventions highlighting the need for a consensus in the field. Agreed cut-offs for designating cognitive impairment could facilitate clinical management including monitoring disease activity, progression, and treatment efficacy.

More Than the Sum of Its Parts: Disrupted Core Periphery of Multiplex Brain Networks in Multiple Sclerosis

Disruptions to brain networks, measured using structural (sMRI), diffusion (dMRI), or functional (fMRI) MRI, have been shown in people with multiple sclerosis (PwMS), highlighting the relevance of regions in the core of the connectome but yielding mixed results depending on the studied connectivity domain. Using a multilayer network approach, we integrated these three modalities to portray an enriched representation of the brain's core-periphery organization and explore its alterations in PwMS. In this retrospective cross-sectional study, we selected PwMS and healthy controls with complete multimodal brain MRI acquisitions from 13 European centers within the MAGNIMS network. Physical disability and cognition were assessed with the Expanded Disability Status Scale (EDSS) and the symbol digit modalities test (SDMT), respectively. SMRI, dMRI, and resting-state fMRI data were parcellated into 100 cortical and 14 subcortical regions to obtain networks of morphological covariance, structural connectivity, and functional connectivity. Connectivity matrices were merged in a multiplex, from which regional coreness-the probability of a node being part of the multiplex core-and coreness disruption index (κ)-the global weakening of the core-periphery structure-were computed. The associations of κ with disease status (PwMS vs. healthy controls), clinical phenotype, level of physical disability (EDSS ≥ 4 vs. EDSS < 4), and cognitive impairment (SDMT z-score < -1.5) were tested within a linear model framework. Using random forest permutation feature importance, we assessed the relative contribution of κ in the multiplex and single-layer domains, in addition to conventional MRI measures (brain and lesion volumes), in predicting disease status, physical disability, and cognitive impairment. We studied 1048 PwMS (695F, mean ± SD age: 43.3 ± 11.4 years) and 436 healthy controls (250F, mean ± SD age: 38.3 ± 11.8 years). PwMS showed significant disruption of the multiplex core-periphery organization (κ = -0.14, Hedges' g = 0.49, p < 0.001), correlating with clinical phenotype (F = 3.90, p = 0.009), EDSS (Hedges' g = 0.18, p = 0.01), and SDMT (Hedges' g = 0.30, p < 0.001). Multiplex κ was the only connectomic measure adding to conventional MRI in predicting disease status and cognitive impairment, while physical disability also depended on single-layer contributions. In conclusion, we show that multilayer networks represent a biologically and clinically meaningful framework to model multimodal MRI data, with disruption of the core-periphery structure emerging as a potential connectomic biomarker for disease severity and cognitive impairment in PwMS.

Functional MRI and cognition in multiple sclerosis-Where are we now?

Multiple sclerosis-related cognitive impairment (MSrCI) affects most patients with multiple sclerosis (MS), significantly contributing to disability and socioeconomic challenges. MSrCI manifests across all disease stages, mainly impacting working memory, information processing, and attention. To date, the underlying mechanisms of MSrCI remain unclear, with its pathogenesis considered multifactorial. While conventional MRI findings correlate with MSrCI, there is no consensus on reliable imaging metrics to detect or diagnose cognitive impairment (CI). Functional MRI (fMRI) has provided unique insights into the brain's neuroplasticity mechanisms, revealing evidence of compensatory mechanisms in response to tissue damage, both beneficial and maladaptive. This review summarizes the current literature on the application of resting-state fMRI (rs-fMRI) and task-based fMRI (tb-fMRI) in understanding neuroplasticity and its relationship with cognitive changes in people with MS (pwMS). Searches of databases, including PubMed/Medline, Embase, Scopus, and the Web of Science, were conducted for the most recent fMRI cognitive studies in pwMS. Key findings ifrom rs-fMRI studies reveal disruptions in brain connectivity and hub integration, leading to CI due to decreased network efficiency. tb-fMRI studies highlight abnormal brain activation patterns in pwMS, with evidence of increased fMRI activity in earlier disease stages as a beneficial compensatory response, followed by reduced activation correlating with increased lesion burden and cognitive decline as the disease progresses. This suggests a gradual exhaustion of compensatory mechanisms over time. These findings support fMRI not only as a diagnostic tool for MSrCI but also as a potential imaging biomarker to improve our understanding of disease progression.

Forceps minor control of social behaviour

The PRISM project, funded by the EU's Innovative Medicines Initiative, has identified a transdiagnostic, pathophysiological relationship between the integrity of the default mode network (DMN) and social dysfunction. To explore the causal link between DMN integrity and social behaviour, we employed a preclinical back-translation approach, using focal demyelination of the forceps minor to disrupt DMN connectivity in mice. By applying advanced techniques such as functional ultrasound imaging and automated analysis of social behaviour, we demonstrated that reduced DMN connectivity leads to impaired social interactions and increased anxiety in mice. Notably, these effects were reversible, indicating that the forceps minor, a critical fibre tract connecting key DMN regions in the prefrontal cortex, plays a crucial role in social function. This study provides direct evidence for a causal relationship between DMN integrity and social dysfunction, with potential implications for developing targeted treatments in precision psychiatry.

The use of 7T MRI in multiple sclerosis: review and consensus statement from the North American Imaging in Multiple Sclerosis Cooperative

The use of ultra-high-field 7-Tesla (7T) MRI in multiple sclerosis (MS) research has grown significantly over the past two decades. With recent regulatory approvals of 7T scanners for clinical use in 2017 and 2020, the use of this technology for routine care is poised to continue to increase in the coming years. In this context, the North American Imaging in MS Cooperative (NAIMS) convened a workshop in February 2023 to review the previous and current use of 7T technology for MS research and potential future research and clinical applications. In this workshop, experts were tasked with reviewing the current literature and proposing a series of consensus statements, which were reviewed and approved by the NAIMS. In this review and consensus paper, we provide background on the use of 7T MRI in MS research, highlighting this technology's promise for identification and quantification of aspects of MS pathology that are more difficult to visualize with lower-field MRI, such as grey matter lesions, paramagnetic rim lesions, leptomeningeal enhancement and the central vein sign. We also review the promise of 7T MRI to study metabolic and functional changes to the brain in MS. The NAIMS provides a series of consensus statements regarding what is currently known about the use of 7T MRI in MS, and additional statements intended to provide guidance as to what work is necessary going forward to accelerate 7T MRI research in MS and translate this technology for use in clinical practice and clinical trials. This includes guidance on technical development, proposals for a universal acquisition protocol and suggestions for research geared towards assessing the utility of 7T MRI to improve MS diagnostics, prognostics and therapeutic efficacy monitoring. The NAIMS expects that this article will provide a roadmap for future use of 7T MRI in MS.

Cognitive impairment in multiple sclerosis: from phenomenology to neurobiological mechanisms

Multiple sclerosis (MS) is an autoimmune-mediated disease of the central nervous system characterized by inflammation, demyelination and chronic progressive neurodegeneration. Among its broad and unpredictable range of clinical symptoms, cognitive impairment (CI) is a common and disabling feature greatly affecting the patients' quality of life. Its prevalence is 20% up to 88% with a wide variety depending on the phenotype of MS, with highest frequency and severity in primary progressive MS. Involving different cognitive domains, CI is often associated with depression and other neuropsychiatric symptoms, but usually not correlated with motor and other deficits, suggesting different pathophysiological mechanisms. While no specific neuropathological data for CI in MS are available, modern research has provided evidence that it arises from the disease-specific brain alterations. Multimodal neuroimaging, besides structural changes of cortical and deep subcortical gray and white matter, exhibited dysfunction of fronto-parietal, thalamo-hippocampal, default mode and cognition-related networks, disruption of inter-network connections and involvement of the γ-aminobutyric acid (GABA) system. This provided a conceptual framework to explain how aberrant pathophysiological processes, including oxidative stress, mitochondrial dysfunction, autoimmune reactions and disruption of essential signaling pathways predict/cause specific disorders of cognition. CI in MS is related to multi-regional patterns of cerebral disturbances, although its complex pathogenic mechanisms await further elucidation. This article, based on systematic analysis of PubMed, Google Scholar and Cochrane Library, reviews current epidemiological, clinical, neuroimaging and pathogenetic evidence that could aid early identification of CI in MS and inform about new therapeutic targets and strategies.

The Prevalence of Cognitive Impairment in Relapsing-Remitting Multiple Sclerosis: A Systematic Review and Meta-analysis

It is increasingly recognized that cognitive symptoms are a common sequelae of relapsing-remitting multiple sclerosis and are associated with adverse functional consequences. However, estimates of cognitive impairment (CIm) prevalence vary widely. This study aimed to determine the pooled prevalence of CIm among adults with RRMS and investigate moderators of prevalence rates. Following prospective registration (PROSPERO; CRD42021281815), electronic databases (Embase, Scopus, Medline, and PsycINFO) were searched from inception until March 2023. Eligible studies reported the prevalence of CIm among adults with RRMS, as determined through standardized neuropsychological testing and defined as evidence of reduced performance across at least two cognitive domains (e.g., processing speed, attention) relative to normative samples, healthy controls, or premorbid estimates. The electronic database search yielded 8695 unique records, of which 50 met selection criteria. The pooled prevalence of cognitive impairment was 32.5% (95% confidence interval 29.3-36.0%) across 5859 participants. Mean disease duration and age were significant predictors of cognitive impairment prevalence, with samples with longer disease durations and older age reporting higher prevalence rates. Studies which administered more extensive test batteries also reported significantly higher cognitive impairment prevalence. Approximately one third of adults with RRMS experience clinical levels of CIm. This finding supports the use of routine cognitive testing to enable early detection of CIm, and to identify individuals who may benefit from additional cognitive and functional support during treatment planning.

U-fiber diffusion kurtosis and susceptibility characteristics in relapsing-remitting multiple sclerosis may be related to cognitive deficits and neurodegeneration

OBJECTIVES

To evaluate the diffusion kurtosis and susceptibility change in the U-fiber region of patients with relapsing-remitting multiple sclerosis (pwRRMS) and their correlations with cognitive status and degeneration.

MATERIALS AND METHODS

Mean kurtosis (MK), axial kurtosis (AK), radial kurtosis (RK), kurtosis fractional anisotropy (KFA), and the mean relative quantitative susceptibility mapping (mrQSM) values in the U-fiber region were compared between 49 pwRRMS and 48 healthy controls (HCs). The U-fiber were divided into upper and deeper groups based on the location. The whole brain volume, gray and white matter volume, and cortical thickness were obtained. The correlations between the mrQSM values, DKI-derived metrics in the U-fiber region and clinical scale scores, brain morphologic parameters were further investigated.

RESULTS

The decreased MK, AK, RK, KFA, and increased mrQSM values in U-fiber lesions (p < 0.001, FDR corrected), decreased RK, KFA, and increased mrQSM values in U-fiber non-lesions (p = 0.034, p < 0.001, p < 0.001, FDR corrected) were found in pwRRMS. There were differences in DKI-derived metrics and susceptibility values between the upper U-fiber region and the deeper one for U-fiber non-lesion areas of pwRRMS and HCs (p < 0.05), but not for U-fiber lesions in DKI-derived metrics. The DKI-derived metrics and susceptibility values were widely related with cognitive tests and brain atrophy.

CONCLUSION

RRMS patients show abnormal diffusion kurtosis and susceptibility characteristics in the U-fiber region, and these underlying tissue abnormalities are correlated with cognitive deficits and degeneration.

CLINICAL RELEVANCE STATEMENT

The macroscopic and microscopic tissue damages of U-fiber help to identify cognitive impairment and brain atrophy in multiple sclerosis and provide underlying pathophysiological mechanism.

KEY POINTS

• Diffusion kurtosis and susceptibility changes are present in the U-fiber region of multiple sclerosis. • There are gradients in diffusion kurtosis and susceptibility characteristics in the U-fiber region. • Tissue damages in the U-fiber region are correlated with cognitive impairment and brain atrophy.

Altered neural intrinsic oscillations in patients with multiple sclerosis: effects of cortical thickness

Objective

To investigate the effects of cortical thickness on the identification accuracy of fractional amplitude of low-frequency fluctuation (fALFF) in patients with multiple sclerosis (MS).

Methods

Resting-state functional magnetic resonance imaging data were collected from 31 remitting MS, 20 acute MS, and 42 healthy controls (HCs). After preprocessing, we first calculated two-dimensional fALFF (2d-fALFF) maps using the DPABISurf toolkit, and 2d-fALFF per unit thickness was obtained by dividing 2d-fALFF by cortical thickness. Then, between-group comparison, clinical correlation, and classification analyses were performed in 2d-fALFF and 2d-fALFF per unit thickness maps. Finally, we also examined whether the effect of cortical thickness on 2d-fALFF maps was affected by the subfrequency band.

Results

In contrast with 2d-fALFF, more changed regions in 2d-fALFF per unit thickness maps were detected in MS patients, such as increased region of the right inferior frontal cortex and faded regions of the right paracentral lobule, middle cingulate cortex, and right medial temporal cortex. There was a significant positive correlation between the disease duration and the 2d-fALFF values in the left early visual cortex in remitting MS patients (r = 0.517, Bonferroni-corrected, p = 0.008 × 4 < 0.05). In contrast with 2d-fALFF, we detected a positive correlation between the 2d-fALFF per unit thickness of the right ventral stream visual cortex and the modified Fatigue Impact Scale (MFIS) scores (r = 0.555, Bonferroni-corrected, p = 0.017 × 4 > 0.05). For detecting MS patients, 2d-fALFF and 2d- fALFF per unit thickness both performed remarkably well in support vector machine (SVM) analysis, especially in the remitting phase (AUC = 86, 83%). Compared with 2d-fALFF, the SVM model of 2d-fALFF per unit thickness had significantly higher classification performance in distinguishing between remitting and acute MS. More changed regions and more clinically relevant 2d-fALFF per unit thickness maps in the subfrequency band were also detected in MS patients.

Conclusion

By dividing the functional value by the cortical thickness, the identification accuracy of fALFF in MS patients was detected to be potentially influenced by cortical thickness. Additionally, 2d-fALFF per unit thickness is a potential diagnostic marker that can be utilized to distinguish between acute and remitting MS patients. Notably, we observed similar variations in the subfrequency band.

Functional MRI-specific alterations in frontoparietal network in mild cognitive impairment: an ALE meta-analysis

Background

Mild cognitive impairment (MCI) depicts a transitory phase between healthy elderly and the onset of Alzheimer's disease (AD) with worsening cognitive impairment. Some functional MRI (fMRI) research indicated that the frontoparietal network (FPN) could be an essential part of the pathophysiological mechanism of MCI. However, damaged FPN regions were not consistently reported, especially their interactions with other brain networks. We assessed the fMRI-specific anomalies of the FPN in MCI by analyzing brain regions with functional alterations.

Methods

PubMed, Embase, and Web of Science were searched to screen neuroimaging studies exploring brain function alterations in the FPN in MCI using fMRI-related indexes, including the amplitude of low-frequency fluctuation, regional homogeneity, and functional connectivity. We integrated distinctive coordinates by activating likelihood estimation, visualizing abnormal functional regions, and concluding functional alterations of the FPN.

Results

We selected 29 studies and found specific changes in some brain regions of the FPN. These included the bilateral dorsolateral prefrontal cortex, insula, precuneus cortex, anterior cingulate cortex, inferior parietal lobule, middle temporal gyrus, superior frontal gyrus, and parahippocampal gyrus. Any abnormal alterations in these regions depicted interactions between the FPN and other networks.

Conclusion

The study demonstrates specific fMRI neuroimaging alterations in brain regions of the FPN in MCI patients. This could provide a new perspective on identifying early-stage patients with targeted treatment programs.

Systematic review registration

https://www.crd.york.ac.uk/prospero/display_record.php?ID=CRD42023432042, identifier: CRD42023432042.

CNS Border-Associated Macrophages: Ontogeny and Potential Implication in Disease

Being immune privileged, the central nervous system (CNS) is constituted by unique parenchymal and non-parenchymal tissue-resident macrophages, namely, microglia and border-associated macrophages (BAMs), respectively. BAMs are found in the choroid plexus, meningeal and perivascular spaces, playing critical roles in maintaining CNS homeostasis while being phenotypically and functionally distinct from microglial cells. Although the ontogeny of microglia has been largely determined, BAMs need comparable scrutiny as they have been recently discovered and have not been thoroughly explored. Newly developed techniques have transformed our understanding of BAMs, revealing their cellular heterogeneity and diversity. Recent data showed that BAMs also originate from yolk sac progenitors instead of bone marrow-derived monocytes, highlighting the absolute need to further investigate their repopulation pattern in adult CNS. Shedding light on the molecular cues and drivers orchestrating BAM generation is essential for delineating their cellular identity. BAMs are receiving more attention since they are gradually incorporated into neurodegenerative and neuroinflammatory disease evaluations. The present review provides insights towards the current understanding regarding the ontogeny of BAMs and their involvement in CNS diseases, paving their way into targeted therapeutic strategies and precision medicine.

Relating Cognition to both Brain Structure and Function: A Systematic Review of Methods

Introduction: Cognitive neuroscience explores the mechanisms of cognition by studying its structural and functional brain correlates. Many studies have combined structural and functional neuroimaging techniques to uncover the complex relationship between them. In this study, we report the first systematic review that assesses how information from structural and functional neuroimaging methods can be integrated to investigate the brain substrates of cognition. Procedure: Web of Science and Scopus databases were searched for studies of healthy young adult populations that collected cognitive data and structural and functional neuroimaging data. Results: Five percent of screened studies met all inclusion criteria. Next, 50% of included studies related cognitive performance to brain structure and function without quantitative analysis of the relationship. Finally, 31% of studies formally integrated structural and functional brain data. Overall, many studies consider either structural or functional neural correlates of cognition, and of those that consider both, they have rarely been integrated. We identified four emergent approaches to the characterization of the relationship between brain structure, function, and cognition; comparative, predictive, fusion, and complementary. Discussion: We discuss the insights provided in each approach about the relationship between brain structure and function and how it impacts cognitive performance. In addition, we discuss how authors can select approaches to suit their research questions. Impact statement The relationship between structural and functional brain networks and their relationship to cognition is a matter of current investigations. This work surveys how researchers have studied the relationship between brain structure and function and its impact on cognitive function in healthy adult populations. We review four emergent approaches of quantitative analysis of this multivariate problem; comparative, predictive, fusion, and complementary. We explain the characteristics of each approach, discuss the insights provided in each approach, and how authors can combine approaches to suit their research questions.

Altered functional connectivity associated with cognitive impairment in neuromyelitis optica spectrum disorder

BACKGROUND

Cognitive impairment is one of the common symptoms in patients with neuromyelitis optica spectrum disorder (NMOSD). However, the underlying mechanism remains unclear. Resting-state functional magnetic resonance imaging (rs-fMRI) offers the opportunity to reveal the patterns of brain activity in patients with different cognitive states. Accordingly, this study investigated functional connectivity (FC) abnormalities within and between the main cognitive networks in cognitively impaired (CI) patients with NMOSD and their correlations with cognitive performance.

METHODS

Thirty-four patients with NMOSD and 39 healthy controls (HC) were included. Neuropsychological evaluations and rs-fMRI scanning were performed. Patients were classified as CI (n = 16) or cognitively preserved (CP; n = 18) according to neuropsychological evaluations. Seven components representing six main cognitive networks were selected by group independent component analysis. The differences in inter- and intranetwork FC among CI, CP, and HC groups were assessed. The correlation between FC values and neuropsychological data in NMOSD was calculated.

RESULTS

The CI group showed decreased intranetwork connectivity in the posterior default mode network (pDMN) compared with the HC group (P < 0.05, GRF corrected), and decreased internetwork connectivity between the salience network (SN) and pDMN, and between the SN and right frontoparietal network (rFPN) compared with CP and HC groups. The altered FC values were significantly correlated with cognitive performance in the whole NMOSD group.

CONCLUSION

The disconnection within the pDMN and between the SN and pDMN or rFPN might suggest the neural substrates underlying cognitive impairment in NMOSD.

The network collapse in multiple sclerosis: An overview of novel concepts to address disease dynamics

Multiple sclerosis is a neuroinflammatory and neurodegenerative disorder of the central nervous system that can be considered a network disorder. In MS, lesional pathology continuously disconnects structural pathways in the brain, forming a disconnection syndrome. Complex functional network changes then occur that are poorly understood but closely follow clinical status. Studying these structural and functional network changes has been and remains crucial to further decipher complex symptoms like cognitive impairment and physical disability. Recent insights especially implicate the importance of monitoring network hubs in MS, like the thalamus and default-mode network which seem especially hit hard. Such network insights in MS have led to the hypothesis that as the network continues to become disconnected and dysfunctional, exceeding a certain threshold of network efficiency loss leads to a "network collapse". After this collapse, crucial network hubs become rigid and overloaded, and at the same time a faster neurodegeneration and accelerated clinical (and cognitive) progression can be seen. As network neuroscience has evolved, the MS field can now move towards a clearer classification of the network collapse itself and specific milestone events leading up to it. Such an updated network-focused conceptual framework of MS could directly impact clinical decision making as well as the design of network-tailored rehabilitation strategies. This review therefore provides an overview of recent network concepts that have enhanced our understanding of clinical progression in MS, especially focusing on cognition, as well as new concepts that will likely move the field forward in the near future.

Task- and resting-state fMRI studies in multiple sclerosis: From regions to systems and time-varying analysis. Current status and future perspective

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Functional MRI is able to detect adaptive and maladaptive abnormalities at different MS stages.

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Increased fMRI activity is a feature of early MS, while progressive exhaustion of adaptive mechanisms is detected later on in the disease.

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Collapse of long-range connections and impaired hub integration characterize MS network reorganization.

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Time-varying connectivity analysis provides useful and complementary pieces of information to static functional connectivity.

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New perspectives might be the use of multimodal MRI and artificial intelligence.

Multiple sclerosis (MS) is a neurological disorder affecting the central nervous system and features extensive functional brain changes that are poorly understood but relate strongly to clinical impairments. Functional magnetic resonance imaging (fMRI) is a non-invasive, powerful technique able to map activity of brain regions and to assess how such regions interact for an efficient brain network. FMRI has been widely applied to study functional brain changes in MS, allowing to investigate functional plasticity consequent to disease-related structural injury. The first studies in MS using active fMRI tasks mainly aimed to study such plastic changes by identifying abnormal activity in salient brain regions (or systems) involved by the task. In later studies the focus shifted towards resting state (RS) functional connectivity (FC) studies, which aimed to map large-scale functional networks of the brain and to establish how MS pathology impairs functional integration, eventually leading to the hypothesized network collapse as patients clinically progress. This review provides a summary of the main findings from studies using task-based and RS fMRI and illustrates how functional brain alterations relate to clinical disability and cognitive deficits in this condition. We also give an overview of longitudinal studies that used task-based and RS fMRI to monitor disease evolution and effects of motor and cognitive rehabilitation. In addition, we discuss the results of studies using newer technologies involving time-varying FC to investigate abnormal dynamism and flexibility of network configurations in MS. Finally, we show some preliminary results from two recent topics (i.e., multimodal MRI analysis and artificial intelligence) that are receiving increasing attention. Together, these functional studies could provide new (conceptual) insights into disease stage-specific mechanisms underlying progression in MS, with recommendations for future research.

A tractometry principal component analysis of white matter tract network structure and relationships with cognitive function in relapsing-remitting multiple sclerosis

Understanding the brain changes underlying cognitive dysfunction is a key priority in multiple sclerosis (MS) to improve monitoring and treatment of this debilitating symptom. Functional connectivity network changes are associated with cognitive dysfunction, but it is less well understood how changes in normal appearing white matter relate to cognitive symptoms. If white matter tracts have network structure it would be expected that tracts within a network share susceptibility to MS pathology. In the present study, we used a tractometry approach to explore patterns of variance in white matter metrics across white matter (WM) tracts, and assessed how such patterns relate to neuropsychological test performance across cognitive domains. A sample of 102 relapsing-remitting MS patients and 27 healthy controls underwent MRI and neuropsychological testing. Tractography was performed on diffusion MRI data to extract 40 WM tracts and microstructural measures were extracted from each tract. Principal component analysis (PCA) was used to decompose metrics from all tracts to assess the presence of any co-variance structure among the tracts. Similarly, PCA was applied to cognitive test scores to identify the main cognitive domains. Finally, we assessed the ability of tract co-variance patterns to predict test performance across cognitive domains. We found that a single co-variance pattern which captured microstructure across all tracts explained the most variance (65% variance explained) and that there was little evidence for separate, smaller network patterns of pathology. Variance in this pattern was explained by effects related to lesions, but one main co-variance pattern persisted after this effect was regressed out. This main WM tract co-variance pattern contributed to explaining a modest degree of variance in one of our four cognitive domains in MS. These findings highlight the need to investigate the relationship between the normal appearing white matter and cognitive impairment further and on a more granular level, to improve the understanding of the network structure of the brain in MS.

Diffusion Tensor Imaging Revealed Microstructural Changes in Normal-Appearing White Matter Regions in Relapsing–Remitting Multiple Sclerosis

Background

Axons and myelin sheaths are the physical foundation for white matter (WM) to perform normal functions. Our previous study found the metabolite abnormalities in frontal, parietal, and occipital normal-appearing white matter (NAWM) regions in relapsing–remitting multiple sclerosis (RRMS) patients by applying a 2D 1H magnetic resonance spectroscopic imaging method. Since the metabolite changes may associate with the microstructure changes, we used the diffusion tensor imaging (DTI) method to assess the integrity of NAWM in this study.

Method

Diffusion tensor imaging scan was performed on 17 clinically definite RRMS patients and 21 age-matched healthy controls on a 3.0-T scanner. DTI metrics including fractional anisotropy (FA), mean diffusivity (MD), axial diffusivity (AD), and radial diffusivity (RD) were extracted from 19 predefined regions of interest (ROIs), which were generated by removing a mask of manually drawn probabilistic lesion map from the Johns Hopkins University white-matter atlas. The mean values of FA, MD, AD, and RD were compared between different groups in the same ROIs.

Results

A probabilistic lesion map was successfully generated, and the lesion regions were eliminated from the WM atlas. We found that the RRMS patients had significantly lower FA in the entire corpus callosum (CC), bilateral of anterior corona radiata, and right posterior thalamic radiation (PTR). At the same time, RRMS patients showed significantly higher MD in the bilateral anterior corona radiata and superior corona radiata. Moreover, all AD values increased, and the bilateral external capsule, PTR, and left tapetum NAWM show statistical significance. What is more, all NAWM tracts showed increasing RD values in RRMS patients, and the bilateral superior corona radiata, the anterior corona radiata, right PTR, and the genu CC reach statistical significance.

Conclusion

Our study revealed widespread microstructure changes in NAWM in RRMS patients through a ready-made WM atlas and probabilistic lesion map. These findings support the hypothesis of demyelination, accumulation of inflammatory cells, and axonal injury in NAWM for RRMS. The DTI-based metrics could be considered as potential non-invasive biomarkers of disease severity.